Coherence Threshold Behaviour Under Perturbation: Empirical Demonstration Using a Minimal Interpretive Model

This dataset contains the empirical results, code, and documentation for a minimal computational experiment evaluating how coherence changes underincreasing perturbation noise. The experiment provides a concrete demonstration of the thresholdbehavior described in the Lattice CoherenceTheorem, where coherence collapses sharply once perturbation exceeds a system’s capacity to maintain internal alignment. A simple interpretive-driven model was used to generate a sequence of internal activation states. Noise was injected at controlled levels between 0.0 and 1.0, and coherence was quantified using mean cosine similarity across activations. The resulting data reveal a clear threshold structure: high coherence at low perturbation, followed by a rapid drop as noise surpasses a critical range. This pattern aligns with theoretical predictions that coherence emerges when interpretive stability dominates perturbation, and collapses when perturbation load becomes excessive. This dataset includes: coherence_vs_noise.csv — recorded noise levels and corresponding coherence values boids_threshold_experiment.ipynb — full code for simulation, CSV generation, and plotting methods.txt — detailed methodological description and reproducibility notes README.txt — overview, context, and usage instructions Plot images — visualizations of the coherencedecline and threshold behavior Together, these files provide a fully reproducible pipeline demonstrating threshold-driven coherencetransitions in adaptive systems. The dataset is suitable for validation, re-analysis, or incorporation into theoretical work on coherence, emergence, synchrony, or perturbation dynamics.